The black box nature of many AI systems
obscures decision-making processes. This can conceal biases, dubious correlations, and other deficiencies, which come to light especially in the cases of dataset shift [1]}
and adversarial examples [2]}, [3]}.
Furthermore, this disparity in transparency has led to unexpected prejudices in real-world applications, including health care and criminal justice [4]}, [5]}.
If this is not motivation enough for reconciliation,
current and forthcoming regulation will require transparency and a right to explanation, such as the EU General Data Protection Regulation [6]},
the US draft
“Guidance for Regulation of [AI] Applications” [7]},
and a United Nations prospective publication [8]}.
